Lecture 1: Data Communication
Nick Huntington-Klein
29 March, 2020
Data Communication
Welcome to Data Communication!
Data Communication
This class is about
- How to turn data into a message
- How to cleanly communicate that message
- Technically, how to create that communication
Admin
Let’s do some housekeeping:
- Course website
- Syllabus
- Expectations and assignments
Resources
In addition to the course website and Knaflic’s Storytelling with Data:
What is Data Communication?
- There is a lot of information in the world
- And a lot of information at your fingertips
- Too much
- And so we simplify to tell the story underlying the data
The Map and the Territory
- Someone asks you for directions to Dick’s on Broadway
- Do you hand them your 3.2GB perfectly detailed shapefile of Capitol Hill?
- The answer is in there, and much more precisely than you could possibly tell them
- But it doesn’t really answer their question, right?
The Map and the Territory
- The goal of a data analyst is to take that shapefile and figure out how to get to Dick’s
- The goal of a data communicator is to take what the data analyst figured out and figure out what part of the map to show you to help you understand how to get to Dick’s
- A good data communicator will make understanding the directions easy and obvious
Goals
- Figure out what the question is (you \(\leftarrow\) them)
- Explore the data to answer the question (analysis)
- (don’t use the data to get the answer you want!)
- Make the viewer understand the answer and why that’s the answer (you \(\rightarrow\) them)
Storytelling With Data
- Understand the context
- Choose an appropriate visual display
- Eliminate clutter
- Focus attention where you want it
- Think like a designer
- Tell a story
Outside of Data
- Let’s consider some examples of effective communication of information outside the narrow range of “data communication”
How Does This Faucet Work?

Understand the context
The person who designed this faucet understands, hopefully, how water pipes work and how opening a valve can allow water to flow
They know what is important for the audience to know - how they can turn the water on
Choose an appropriate visual display
We have a handle close to the source of the water
It implies the ways the handle can be turned - towards us or away, left and right
The display doesn’t allow us any information about how those directions relate to pressure or temperature
(what version of a faucet might?)
Eliminate clutter
Nothin’ but handle
We could have other stuff here - sink stopper, an LCD with the weather report, but do we need it?
Focus attention where you want it
There’s nowhere to look but the handle (other than the spigot, not pictured)
The shape and design pushes you towards it - it calls for a hand!
Think like a designer
We want the user to understand that they can pull or rotate the handle to affect the water flow
This design affords both of those uses
And nothing else
There aren’t a lot of ways to use this wrong, other than messing up pressure vs. temperature
Tell a story
Water flow can be controlled by twisting this handle
If you were a monkey who had never experienced plumbing, it would only take you about ten seconds to follow the design to that handle, pull it, and learn about the connection between handles and water flow
Gapminder
- Let’s move into some data
- Gapminder (from the Gapminder institute) is a data set that, among other things, shows how differences between countries change over time
- One thing it is commonly used to show is that economic development aids health development
- GDP per capita \(\rightarrow\) life expectancy
- Also, generally, both of those things have improved over time
Gapminder
## # A tibble: 1,704 x 6
## country continent year lifeExp pop gdpPercap
## <fct> <fct> <int> <dbl> <int> <dbl>
## 1 Afghanistan Asia 1952 28.8 8425333 779.
## 2 Afghanistan Asia 1957 30.3 9240934 821.
## 3 Afghanistan Asia 1962 32.0 10267083 853.
## 4 Afghanistan Asia 1967 34.0 11537966 836.
## 5 Afghanistan Asia 1972 36.1 13079460 740.
## 6 Afghanistan Asia 1977 38.4 14880372 786.
## 7 Afghanistan Asia 1982 39.9 12881816 978.
## 8 Afghanistan Asia 1987 40.8 13867957 852.
## 9 Afghanistan Asia 1992 41.7 16317921 649.
## 10 Afghanistan Asia 1997 41.8 22227415 635.
## # ... with 1,694 more rows
Understand the Context
What do we want people to learn?
- GDP per capita and life expectancy go together strongly
- Both GDP per capita and life expectancy have increased a lot over time
Choose an appropriate visual display
- We want something that will show a relationship between two variables with many observations
![]()
Eliminate clutter
- That’s a lot of dots! Can we tell the same story by focusing on just a few countries?
- Also, that’s a lot of background ink…
![]()
Focus attention where you want it
- Those few high-GDP observations are drawing a LOT of space, as opposed to that left blob. Let’s put the x-axis on a log scale
![]()
Think like a designer
- Why make the reader work?
- Also, realize this graph sort of feels like it’s moving forward in time. Uh-oh…
![]()
Tell a story
- Realize that we’ve lost the “things get better over time” angle
- And also lost the part where we want to talk about the whole world!
- Use what we’ve done so far to think about how we can show the dual GDP-and-life-expectancy improvements over time for everyone
What could still be improved?
![]()
Let’s See What We Can Get